The Use of Linear Prediction for the Interpolation and Extrapolation of Missing Data and Data Gaps Prior to Spectral Analysis

摘要

The spectral analysis of a series of equally spaced samples of a time-stationary process becomes difficult when samples are missing or sizable data gaps occur within the interval of interest. A linear prediction algorithm can be used to fill in the missing data with estimates that are spectrally consistent with the data that are observed. Simulated and practical radar examples demonstrate an improvement in resolution and a reduction of sidelobe interference levels. Computer programs are provided which accomplish the extrapolation and interpolation for complex data. (Author)